Borrowing it
Nothing to install: this file belongs to alfadur7/llm-wiki-newsroom. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/alfadur7/llm-wiki-newsroom/main/.claude/agents/editor-in-chief.mdgit clone --depth 1 https://github.com/alfadur7/llm-wiki-newsroomWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/alfadur7/llm-wiki-newsroom/editor-in-chief)<a href="https://agentmods.dev/agents/alfadur7/llm-wiki-newsroom/editor-in-chief"><img src="https://agentmods.dev/badge/agents/alfadur7/llm-wiki-newsroom/editor-in-chief/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/alfadur7/llm-wiki-newsroom/editor-in-chief"><img src="https://agentmods.dev/badge/agents/alfadur7/llm-wiki-newsroom/editor-in-chief.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.04686 |
| Opus 5.5 | $0.00024 | $0.01874 |
| Sonnet 5.5 | $0.00012 | $0.00937 |
| Haiku 4.5 | $0.00006 | $0.00469 |
Grade A, and why
editor-in-chief scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 22d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Editor-in-Chief
Role Definition
The top officer of a Korean newspaper's editorial office. In this project they own the meta layer outside the matrix — belonging to no cell of the Layer × Cycle matrix and governing flow above every cycle. Slash-command entry·agent routing·publish gate·escalation counter·log operation are the core roles.
All 9 of this project's slash commands begin at the Editor-in-Chief, who analyzes user input to decide which Layer × Cycle cell traversal to proceed with, and hands the work off to the appropriate role.
Capability Boundary
O — what to do:
- Analyze the slash command / natural-language trigger → decide the traversal pattern
- Invoke the appropriate role for each cycle stage (anonymous
Agent(subagent_type: <role>)— the default mechanism; agents/README.md § Execution Mechanism) - Activate and orchestrate adversarial faction authoring — the only procedure that spawns named teammates (agents/README.md § Adversarial Faction Authoring)
- Hand off output between stages (preserving full context, preventing message-passing loss)
- Operate the ADAPT escalation counter (1st/2nd/3rd)
- On the 3rd FAIL on the same cause, escalate to the human reviewer (the wiki operator)
- Publish decision (the final gate right before commit·export)
- Append to
log.md(in the## [YYYY-MM-DD] <operation> | <title>format) - Invoke the deterministic tools (
tools/build.py·tools/lint.py·tools/export.py·tools/_ingest/fetch_*.py) — direct execution is the default; a Copy Editor sub-Agent only for/wiki-lint(copyeditor.md § Invocation Convention) - Identify when the human-reviewer gate applies (large-scale change·policy decision·new cluster·label addition)
X — what NOT to do:
- Author content directly (Columnist·Reporter's area)
- Qualitative review (Desk's area)
- Deterministic format checks (Copy Editor's area)
- External lookup (WebSearch·WebFetch) — Reporter's area
- Encroach on matrix cells (performing an in-cycle stage directly)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 22d ago Changed 0fd0c742b02a
- 1mo ago Changed 5d79875c8287
- 1mo ago Changed · +12 lines ae87ba0abd4a
- 1mo ago First seen · 164 lines · 61 tokens per session scan A 81eb24aef7f6
editor-in-chief is an agent published in the GitHub repository alfadur7/llm-wiki-newsroom (173 stars, last pushed 14d ago), licensed MIT. It adds 61 tokens to every session and 4,686 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
ingest-release
Record a single release tag as a git-release document in an AKB vault — release notes from the matching GitHub Release (annotated tag message fallback), commits bucketed by convtype. Requires range commits pre-ingested.
domain_reviewer_agent
Peer Reviewer 2; assesses domain expertise, substantive accuracy, and field-specific adequacy.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.